Fuzzy Time Series Lee dengan Average Based Length untuk Prediksi Jumlah Penduduk Miskin Sulawesi Tenggara
DOI:
https://doi.org/10.55340/japm.v9i1.1270Keywords:
FTS, average based length, forcastingAbstract
This study aims to predict the number of poor people in Southeast Sulawesi using the Lee’s Fuzzy Time Series with Average Based Length. The data used in this research is annual periodic data from 2004-2022 downloaded from the bps.go.id website. The results of the study show that the poverty rate in Southeast Sulawesi in 2023 will reach 301,801 people. The model is successful in reading data movements, with the number of error values > 0 indicating the direction of prediction error which tends to be underestimated. However, the resulting accuracy is very good, indicated by the MAPE value of 1.71%.
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References
Rahmawati dkk. (2020). Prediksi Jumlah Wisatawan di Kota Pekanbaru pada Tahun 2019-2023 dengan Menggunakan Metode Fuzzy Time Series Chen. Theta: Jurnal Pendidikan Matematika Vol. 2 No. 1 April 2020. 2020. ISSN 2656-7172.
https://journal.umbjm.ac.id/index.php/THETA/article/view/512
Solikhin & Yudatama, U. 2019. Fuzzy Time Series dan Algoritma Average-Based Length untuk Prediksi Pekerja Migran Indonesia. Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) Vol. 6, No. 4, Agustus 2019, hlm 369 – 376.
http://dx.doi.org/10.25126/jtiik.2019641177
Nabillah, I. & Ranggadara, I. (2020). Mean Absolut Precentage Error untuk Evaluasi Hasil Prediksi Komuditas Laut. Journal of Information System Vol. 5, No. 2, November 2020, hlm 250–255. DOI: 10.33633/joins.v5i2.3900
